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Application of the Deep Learning Algorithm and Similarity Calculation Model in Optimization of Personalized Online Teaching System of English Course.

Computational intelligence and neuroscience
This study provides an in-depth study and analysis of English course recommendation techniques through a combination of bee colony algorithm and neural network algorithm. In this study, the acquired text is trained with a document vector by a deep le...

Optimization of Machine Online Translation System Based on Deep Convolution Neural Network Algorithm.

Computational intelligence and neuroscience
In order to effectively optimize the machine online translation system and improve its translation efficiency and translation quality, this study uses the deep separable convolution neural network algorithm to construct a machine online translation m...

Application of Dynamic Process Neural Network Model Identification in Ethnic Dance Online Teaching System.

Computational intelligence and neuroscience
With the development of the times, education presents a new trend, but the teaching characteristics of dance classroom teaching cannot adapt to the current development trend. In this article, the author analyzes modern information technology, hoping ...

Online Detection System for Wheat Machine Harvesting Impurity Rate Based on DeepLabV3.

Sensors (Basel, Switzerland)
Wheat, one of the most important food crops in the world, is usually harvested mechanically by combine harvesters. The impurity rate is one of the most important indicators of the quality of wheat obtained by mechanized harvesting. To realize the onl...

Memristor-based spiking neural network with online reinforcement learning.

Neural networks : the official journal of the International Neural Network Society
Neural networks implemented in memristor-based hardware can provide fast and efficient in-memory computation, but traditional learning methods such as error back-propagation are hardly feasible in it. Spiking neural networks (SNNs) are highly promisi...

AI Supporting AAC Pictographic Symbol Adaptations.

Studies in health technology and informatics
The phenomenal increase in technological capabilities that allow the design and training of systems to cope with the complexities of natural language and visual representation in order to develop other formats is remarkable. It has made it possible t...

Online Privacy-Preserving EEG Classification by Source-Free Transfer Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Electroencephalogram (EEG) signals play an important role in brain-computer interface (BCI) applications. Recent studies have utilized transfer learning to assist the learning task in the new subject, i.e., target domain, by leveraging beneficial inf...

Online monitoring of Haematococcus lacustris cell cycle using machine and deep learning techniques.

Bioresource technology
Optimal control and process optimization of astaxanthin production from Haematococcuslacustris is directly linked to its complex cell cycle ranging from vegetative green cells to astaxanthin-rich cysts. This study developed an automated online monito...

Online Unsupervised Adaptation of Latent Representation for Myoelectric Control During User-Decoder Co-Adaptation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Myoelectric control interfaces, which map electromyographic (EMG) signals into control commands for external devices, have applications in active prosthesis control. However, the statistical characteristics of EMG signals change over time (e.g., beca...

Online ensemble model compression for nonstationary data stream learning.

Neural networks : the official journal of the International Neural Network Society
Learning from data streams that emerge from nonstationary environments has many real-world applications and poses various challenges. A key characteristic of such a task is the varying nature of the underlying data distributions over time (concept dr...